Psychological engagement with automated design improvement feedback: a multiple case study of ChatGPT in design education

The findings extend self-regulated learning theory to human-AI contexts, revealing how metacognitive capabilities shape behavioral, cognitive, and emotional engagement with AI feedback. Results demonstrate the need for scaffolding interventions to support lower-performing students in developing metacognitive strategies for effective AI interaction. This study contributes initial insights into performance-based variations in human-AI collaboration within educational contexts.